Method for controlling a medical imaging examination of a subject, medical imaging system and computer-readable data storage medium

ABSTRACT

The method comprises receiving an image sequence of the subject from the camera during the medical imaging scan; receiving at least one of the current position or velocity of the patient table during the medical imaging scan; performing a motion tracking analysis of the image sequence to extract a motion model, wherein at least one of the motion tracking analysis or the motion model is tailored to the body region of interest and takes into account the at least one of the current patient table position or velocity; and analysing the motion model to detect subject motion and, if the detected motion is above a threshold, at least one of adapting the medical imaging examination or issuing an alert.

CROSS-REFERENCE TO RELATED APPLICATION(S)

The present application claims priority under 35 U.S.C. § 119 toEuropean Patent Application No. EP 21176876.7, filed May 31, 2021, theentire contents of which are incorporated herein by reference.

FIELD

Embodiments of the present invention relate to a method for controllinga medical imaging examination of a subject, a medical imaging systemhaving a gantry, a patient table which is moveable with respect to thegantry, a camera disposed above the patient table and a control unit,and a non-transitory computer-readable data storage medium.

BACKGROUND

Despite the huge progress in medical imaging acquisition speed, patientmotion such as breathing or unintended body movements still causemotion-induced image artefacts. In the present clinical routine,patients are asked not to move or to hold their breath for a period oftime during the medical imaging scan. However, this poses a challenge toa number of patients who are not able to comply with this because oftheir health impairments. Hence, there is need that the medical imagingsystem adapts to the patient motion. There already exist some algorithmsto compensate for motion in the medical image reconstruction, forexample D. Schäfer, J. Borgert, V. Rasche and M. Grass“Motion-Compensated and Gated Cone Beam Filtered Back-Projection for 3-DRotational X-Ray Angiography”, IEEE Transactions on Medical Imaging,vol. 25, no. 7, July 2006. However, this motion correctionreconstruction method assumes that a motion vector for every voxel isknown.

SUMMARY

The inventors have identified that it is a challenge is to track andquantify the patient motion during a scan. For respiratory motiontracking, simplified measurement systems exist, such as fixation beltsto position a pressure transducer, or laser scanners. However, theinventors have determined that these devices complicate the scanworkflow and are mainly used for therapy-related imaging such asradiation therapy planning, as they are too complex for routine clinicalimages.

Embodiments of the present invention provide a simpler approach to trackand quantify patient motion, which does not place a burden or take uptime of the operating staff of the medical imaging system. Embodimentsof the present invention also more adequately adapt the medical imagingexamination to the estimated patient motion.

An embodiment of the present invention provides a method for controllinga medical imaging examination of a subject, wherein the medical imagingexamination comprises performing a medical imaging scan of a body regionof interest of the subject using a pre-selected scan protocol, whereinthe medical imaging examination is performed using a medical imagingsystem having a gantry, a patient table which is moveable with respectto the gantry and on which the subject is positioned, a control unit forcontrolling the medical imaging scan and having access to an imagesequence of the subject acquired by a camera, and wherein the methodcomprises the steps of receiving an image sequence of the subject fromthe camera during the medical imaging scan; receiving the currentposition and/or velocity of the patient table during the medical imagingscan; performing a motion tracking analysis of the received imagesequence to extract a motion model, wherein the motion tracking analysisand/or the motion model is tailored to the body region of interest andtakes into account the current patient table position and/or velocity;analysing the motion model to detect subject motion and, for example ifthe detected motion is above a pre-determined threshold, adapting themedical imaging examination to the detected motion and/or issuing analert to make the subject and/or an operator of the medical imagingsystem aware of the detected motion.

The method uses a camera-based approach to track and quantify patientmotion and further uses the intrinsic knowledge of the system about thescan protocol and/or the motion of the patient table to adequately adaptthe medical imaging examination to the estimated patient motion.

The medical imaging examination may be any clinical medical imagingexam, including angiography or radiation therapy planning. The medicalimaging examination may comprise one or several medical imaging scans,wherein each medical imaging scan acquires medical images from a bodyregion of interest of the subject using a pre-selected scan protocol.The scan protocol may be pre-selected by the radiologist or a doctorordering the medical imaging examination and may already specify thebody region of interest, as well as scan parameters. The scan parametersmay include the resolution, slice thickness, dose, radiation energy andwhether or not contrast agent is to be applied. Thus, the scan protocolmay be tailored to the diagnostic question (for example trauma, tumour,blood vessels, stroke), as well as the body region of interest on whichthe medical imaging scan is to be performed.

The medical imaging system has a gantry and a patient table which ismoveable with respect to the gantry and on which the subject is lying,usually in a supine position. According to an embodiment, the gantrycomprises an X-ray source and an X-ray detector, which are rotatablearound the patient table. According to an embodiment, the gantrycomprises a superconducting magnet in form of a hollow cylinder, intowhich the patient table can be inserted along an axial direction.

In some embodiments, the gantry is stationary, and the patient table ismoveable at least in axial direction (z-direction) through the gantry.However, embodiments of the present invention are also applicable tomedical imaging system with a moveable, e.g., slidable, gantry, whereinthe patient table may be stationary or may also be moveable. Gantry andpatient table are usually moveable at least in z-direction with respectto each other. The medical imaging system further comprises a controlunit for controlling the medical imaging scan, which may be part of acomputer system. The control unit has access to image sequences acquiredby a camera disposed above the subject. The motion tracking analysisaccording to embodiments of the present invention may also be performedby the control unit, or by another processing unit, which may also bepart of the computer system and which is connected via a data link tothe control unit. Thus, the processing unit may be the or part of thecontrol unit.

The camera may be fixed to the gantry and may be integrated into themedical imaging system. It may be disposed somewhere above the patienttable. It may be mounted on a separate stand or at the ceiling above thepatient table. Thus, the camera may be stationary with respect to thegantry, or alternatively with respect to the patient table. The cameramay be an optical camera, in particular a digital or video cameracapable of acquiring a time sequence of images of the patient while heis positioned on the patient table. The time resolution is preferablysufficient to capture relevant movement during the scan, for example2-120 frames per second. The camera may be a camera already integratedin state-of-the art medical imaging systems, which today is used simplyfor visual patient monitoring. According to embodiments of the presentinvention, the control unit receives not only the image sequence fromthe camera during the medical imaging scan but is also aware of orreceives the current position and/or velocity of the patient table, andoptionally also the pre-selected scan protocol.

The control unit or processing unit then performs a motion trackinganalysis of the received image sequence to extract a motion model of thebody region of interest of the subject, wherein the motion trackinganalysis and/or the motion model are tailored to the body region ofinterest and take into account the current patient table position and/orvelocity. Thereby, the motion tracking analysis may be simplified andtherefore stabilized, because based on the body region of interest andoptionally the scan protocol to be applied, an appropriate, e.g.,simplified motion model is applied. Already knowing the body region ofinterest also allows to detect the relevant body region on the images(which may have a larger field of view) beforehand.

In the next step, the motion model is analysed to detect subject motion.Preferably, the detected motion is classified as sufficient tocompromise the scan process (e.g., above a pre-determined threshold) oras non-existent or irrelevant. For example, if the threshold is crossed(or always), the medical imaging system may adapt to the motion in amanner specific to the medical imaging examination and optionally scanprotocol and/or body region.

Thus, a camera-based approach is presented to track and quantify patientmotion and to adequately adapt the medical imaging examination to theestimated patient motion. The method exploits specific informationavailable at the medical imaging system, such as the body region to bescanned and optionally the scan protocol to be applied, in order toadequately react to patient motion. The method also incorporatesavailable motion information of the patient table. Embodiments of thepresent invention, thus, provide a method for mitigating the effect ofpatient motion, in which the scan workflow is not negatively impacted byadditional devices or workflow steps to track patient motion.

The motion tracking analysis may utilise machine-learning basedalgorithms to estimate motion on the image sequence. For example,algorithms provided by Google MediaPipe (currently available underhttps://mediapipe.dev) may be used. The algorithms use e.g., neuralnetworks, to extract the position of pre-determined objects on eachimage. Thereby, motion can be estimated directly from the RGB imagedata, or in the case of a three-dimensional (3D) camera acquiring imageswith depth information, also form the depth data. In low-end medicalimaging systems, where only two-dimensional (2D) cameras are available,the motion tracking analysis may include deriving the motion from the 2Dimage sequences using a state-of-the art algorithms. By taking intoaccount the current patient table position and/or velocity, the motionmay be corrected for movements of the medical imaging system patienttable, that are explicitly known within the control unit. One correctionapproach is to subtract the table motion from the camera-estimatedoverall motion. This ensures that only patient motion relative to thetable is captured by the camera-based motion estimates.

According to an embodiment, the motion tracking analysis uses a motionmodel which is specific to the selected scan protocol and/or the bodyregion of interest. In some embodiments, the selected scan protocolalready comprises the relevant body region, wherein the body region ofinterest may for example be head, thorax, a limb or part of a limb, hip,neck, shoulder, or any other body part which may be covered by a medicalimaging scan. The motion model may be tailored to the shape, thefeatures and/or the kind of motion that may occur in the specific bodyregion. In particular, the motion model may consider the joints and themovement they allow. For example, the head may, in a firstapproximation, be taken as a rigid body, i.e., it can rotate andpossibly translate, but the skull cannot deform within itself. In asecond approximation, movements of the jaw and throat, such asswallowing, may be incorporated into the model. Motion models of thelimbs may incorporate the possible movement at the joints, whereas amotion model of the thorax will include breathing motion and optionallythe heartbeat. Thus, the motion tracking analysis will specifically lookout for motion which fits the motion model specific to the body regionof interest to be scanned.

The default/general motion model may be a dense, elastic motion fieldcapturing the motion at each image position.

When the motion model is specific to the body region of interest, themotion tracking analysis may comprise detecting and tracking landmarksspecific to the body region of interest in the image sequence, applyinga filter algorithm to the tracked landmarks to compensate inaccuratedetections in one or several of the images of the sequence, inparticular a Kalman filter; correcting the tracked landmarks by theposition and/or velocity of the patient table; and estimating the motionmodel based on the filtered and corrected landmarks.

The landmarks can be detected for example by an algorithm based on atrained neural network. Thus, an appropriate number of landmarks (e.g.,6-300, preferably 40-150) may be pre-defined for each specific bodyregion, wherein the landmarks designate characteristic portions of thebody surface. If the body region is the head, the landmarks may befacial landmarks, which may be used to determine the position of theeyes, nose, and mouth.

Since the landmarks are detected in each image of the sequenceindependently of each other, errors in the detection may lead to abruptchanges from on image to the next, leading to instability. Therefore, afilter algorithm may be applied to the tracked landmarks to compensateinaccurate detections in one or several of the images. In oneembodiment, this may be a Kalman filter, as described for example in G.Welch and G. Bishop “An Introduction to the Kalman Filter”, Sep. 17,1997. A Kalman filter is an algorithm that uses a series of measurementsobserved over time (here: the positions of the tracked landmarks)containing statistical noise and other inaccuracies, to produceestimates of unknown valuables (here: the positions of tracked landmarkson later/future images in the series) that tend to be more accurate thanthose based on a single measurement alone. By using a Kalman filter, themotion of the tracked landmarks can be estimated with higher certaintyand stability. An alternative algorithm is the Sparse Optical Flowalgorithm, for example, as described in J. Barron, D. Fleet and S. S.Beauchemin “Performance of Optical Flow Techniques”, InternationalJournal of Computer vision 12, 43-77 (1994). This technique may be usedto approximate the 2D motion field, i.e., the projection of 3Dvelocities onto the imaging surface, from the image intensity of theimage sequence.

Since the subject motion is being tracked during a medical imaging scan,table movement is expected. To ensure that only the movement of the bodyregion of interest, for example the head, is detected, the positions ofthe tracked landmarks may be corrected according to the patient tablemovement. These table movements (position and/or velocity including thedirection) are explicitly known within the medical imaging system, e.g.,in the control unit. Thus, based on the filtered and correctedlandmarks, a motion model specific to the body region can be estimated.In an embodiment, the motion vectors of the landmarks constitute themotion model.

According to an embodiment, the motion tracking analysis furthercomprises estimating rotation and translation vectors on the basis ofthe positions of the landmarks on each image of the sequence and thecamera parameters, determining the orientation and movement of the bodyregion of interest, in particular the head, based on the detectedlandmarks and the rotation and translation vectors. From the position ofthe landmarks and the known intrinsic parameters of the camera, inparticular the camera's position and orientation with respect to thepatient table, rotation and translation vectors can be estimated. Thesetranslation and rotation vectors may for example apply to a body regionwhich may be assumed to be a rigid body, such as the head. In this case,only 6 degrees of freedom (three translation vectors and the three Eulerangles) need to be estimated for each time point.

For this purpose, a direct linear transform solution with the knownintrinsic parameters of the camera could be applied. In this process,each landmark of the body of interest in the world coordinate system isprojected onto the image plane to consider the orientation and positionof the body from an image sequence to the camera. To minimize projectionerrors, a Levenberg-Marquart optimisation could be applied toiteratively adjust the rotation and translation vectors. Furthermore,the resulting vectors and the intrinsic parameters of the camera may beused to calculate the Euler angles. Consequently, the orientation andmovement of the head may be checked based on the determined faciallandmarks, vectors and angles.

According to an embodiment, the method comprises a step of correctingthe motion model or the motion vector field by the patient tablevelocity. This may be done by correcting the motion model, in particularthe position for the landmarks and motion vectors, by estimating thetranslation using the current position and/or velocity of the patienttable. Thereby, the table motion in the images in the images may becompensated by shifting the image content by the table motion. Further,the control unit may identify the current patient table position, andonly once the table position is close to the target position for theexamination, the motion tracking analysis is started. In anotherembodiment, the threshold for motion recognition may be corrected by thepatient table velocity.

According to an embodiment, the motion tracking analysis is started onlyonce the patient table has reached a target position for theexamination. Usually, the patient will lie down on the patient tablewhile it is disposed outside the gantry, and then the patient table willbe shifted at least in z-direction into the gantry, to a target positionfor this examination, e.g., such that the body region of interest isinside the gantry. By starting the motion tracking approach only oncethe patient table is at the target position, the calculation effort forcorrecting fast table motion may be reduced.

In the event that the body region is the thorax, the motion trackinganalysis may comprise the extraction of a one-dimensional (1D) model ofupwards and downwards motion of the thorax from the image sequenceacquired by a three-dimensional camera. This implies that depthinformation is available, and in this case the upward/downward motionmay provide an adequate model of breathing. For example, the motiontracking analysis may comprise a step of averaging the depth (i.e.,distance from the camera) of the chest over a pre-defined area on eachimage of the sequence, and optionally using a Kalman filter to predictthe further breathing motion. Since the breathing motion is cyclic,extrapolation of the movement is possible.

The motion tracking analysis may comprise a step of applying a densemotion tracking approach to the sequence of images to estimate a motionvector field, in particular by using an optical flow technique. Thisapproach is advantageous in particular in case only 2-D camera motiontracking is available. This may be followed by correcting the motionvector field by the patient table velocity. From the motion field, thebreathing motion may be extracted as follows:

According to an embodiment, the motion vector field is calculated firstin a coarse resolution, followed by a calculation by one or severalfiner resolutions. In other words, the analysis may be performed in amulti-resolution fashion to obtain a global breathing model at a coarselevel, but and detect further movements at the finer resolutions. In anexample, the image sequence may have a resolution of 640×1080 pixels.However, in the first step, it is sampled to a much lower resolution, inorder to estimate motion on a large scale first. This has the advantagethat aliasing is suppressed. When the main movements have beenidentified, the analysis is repeated on a finer resolution, to furtherdifferentiate detected motion.

According to an embodiment, the motion tracking analysis may furthercomprise the steps of analysing the orientation of the motion vectorfield for detecting inward and outward motion, in particular bycalculating the divergence of the motion vector field, and on this basisestimating a motion model of breathing motion.

This is based on the insight that inspiration and expiration can bedifferentiated by analysing the orientation of the motion vectors: atthe sides of the body, inspiration, i.e., an expansion of the chest, ischaracterized by motion vectors pointing towards the boundaries of theimage. During expiration, i.e., contraction of the chest, the motionvectors point towards the centre. Mathematically, this may becharacterised by the divergence of the vector field, a positive valueindicates an expansion of the chest (inspiration), a negative valueindicating expiration.

Further, a secondary breathing motion in z-direction may be observed inthe waist region or the shoulder region. For the shoulders, inspirationleads to a shift towards the head, whereas expiration leads to amovement towards the feet. At the waist, the motion may be upwards ordownwards for inspiration, depending on whether chest or abdominalbreathing is dominant. Nevertheless, the movement in z-direction at thewaist may be valuable to support the detection of breathing and todifferentiate between chest and abdominal breathing if the generalphases of inspiration/expiration are detected from the body sides or theshoulders. The magnitude of the motion vector field describes the amountof breathing motion. The above-described multi-resolution analysis maybe used to be able to differentiate between abdominal and chestbreathing in the finer resolutions.

Based on the detected motion, in particular whether the motion crosses athreshold, the medical imaging system may react and adapt the medicalimaging examination in on or more ways.

According to an embodiment, the medical imaging system may issue analert to the subject and/or the operator. For example, the operator,i.e., a technician or radiological assistant, may receive a visual oracoustic warning. The visual warning can be realized as a colour overlayon the live image shown on the scanner tablet. The alert may include thekind of detected motion, and suggestions for action. For example, tore-position the patient, or to instruct the patient to counteract themovement. Alternatively, the subject may be made aware of the motionthrough a visual or acoustic warning. According to an embodiment, thealert issued to the subject may comprise the kind of motion and/or asuggestion for correcting the motion. For example, the alert may includea visual or acoustic sign to catch the subject's attention. Afterwards,one or more of the images acquired by the camera may be displayed to thesubject on a screen, including arrows to indicate how the patient shouldmove in order to correct the inadvertent motion. For example, there maybe an arrow or an acoustic sign, asking him to turn his head back to thecentre, when he/she before turned the head to one side.

According to another embodiment, adapting the medical imagingexamination may comprise re-acquiring the medical imaging data whichwere compromised by the detected motion. The medical imaging data maybe, for example, computed tomography data or magnetic resonance imagingdata.

For example, the patient table may stop or move backwards to allow themedical imaging system to scan the affected portions again. This may benecessary for example when coughing is detected, which is possible usingthe inventive technique. In prior art techniques, only a respiratorysurrogate (i.e., a simplified 1D signal) was detected via the chestbelt, and this could not detect complex movement like coughing. Bydetecting couching in the camera-based inventive approach, re-scanningof certain z-positions may be triggered when necessary.

According to a further embodiment, adapting the medical imagingexamination may comprise performing a motion-compensated imagereconstruction of the medical imaging data (also referred to asmotion-compensated medical image reconstruction), for example amotion-compensated filtered-back projection. In other words, thecamera-based motion estimation may be used as input information forstate-of-the-art motion-compensated reconstruction algorithms, like thealgorithm by Dirk Schafer mentioned above, to correct the reconstructionfor the estimated motion. The medical image reconstruction may be, forexample, a computed tomography image reconstruction or a magneticresonance image reconstruction.

According to an embodiment, the medical imaging examination is acomputed tomography examination (also referred to as a CT examination),the medical imaging scan is a computed tomography scan (also referred toas a CT scan), and the medical imaging system is a computed tomographysystem (also referred to as a CT system).

In particular, a method for controlling a CT examination of a subject isdisclosed herewith, wherein the CT examination comprises performing a CTscan of a body region of interest of the subject using a pre-selectedscan protocol,

wherein the CT examination is performed using a CT system having agantry, a patient table which is moveable with respect to the gantry andon which the subject is positioned, a control unit for controlling theCT scan and having access to an image sequence of the subject acquiredby a camera, and wherein the method comprises the steps of(a) receiving an image sequence of the subject from the camera duringthe CT scan;(b) receiving the current position and/or velocity of the patient tableduring the CT scan;(c) performing a motion tracking analysis of the received image sequenceto extract a motion model, wherein the motion tracking analysis and/orthe motion model is tailored to the body region of interest and takesinto account the current patient table position and/or velocity;(d) analysing the motion model to detect subject motion and, for exampleif the detected motion is above a pre-determined threshold, adapting theCT examination to the detected motion and/or issuing an alert to makethe subject and/or an operator of the CT system aware of the detectedmotion.

According to an embodiment, the medical imaging examination is amagnetic resonance imaging examination (also referred to as an MRIexamination), the medical imaging scan is a magnetic resonance imagingscan (also referred to as an MRI scan), and the medical imaging systemis a magnetic resonance imaging system (also referred to as an MRIsystem).

Embodiments of the present invention are further directed to a medicalimaging system comprising a gantry, a patient table which is moveablewith respect to the gantry, a camera disposed above the patient table ina known position and orientation with respect to the gantry, wherein thecamera is adapted to acquire an image series of a subject positioned onthe patient table, and a control unit for controlling a medical imagingscan. The control unit is adapted to receive an image sequence of thesubject from the camera during the medical imaging scan, and the currentposition and/or velocity of the patient table during the medical imagingscan. The control unit is further adapted for performing a motiontracking analysis of the received image sequence to extract a motionmodel, wherein the motion tracking analysis and/or the motion model istailored to the body region of interest and takes into account thecurrent patient table position and/or velocity; and the control unit isfurther adapted for analysing the motion model to detect subject motionand, for example if the detected motion is above a pre-determinedthreshold, for adapting the medical imaging examination to the detectedmotion and/or for issuing an alert to make the subject and/or anoperator of the medical imaging system aware of the detected motion.

The medical imaging system is adapted for performing the methodaccording to embodiments of the present invention. All features andadvantages described with respect to the method are also applicable tothe medical imaging system and vice versa. The method may be (at leastpartly) carried out by a control unit, which is part of the medicalimaging system, and which receives the image sequence, performs themotion tracking analysis, and may adapt the medical imaging examinationto react to the detected motion.

According to an embodiment, the camera is a video camera or digitalcamera adapted to acquire 2-D. The camera may be integrated into thegantry. Thereby, the position and other intrinsic camera parameters,such as the field-of-view, the imaging angle with respect to the patienttable, the resolution, etc. are automatically known to the medicalimaging system, in particular the control unit.

According to an alternative embodiment, the camera inside is a 3D cameraadapted to acquire images including depth information of the subject.Such 3D cameras may for example include two lenses in order to capturethe body region of interest in two angles, and thereby extractcontour/depth information.

The medical imaging system may be, for example, a computed tomography(CT) system or a magnetic resonance imaging (MRI) system or a positronemission tomography (PET) system or a C-arm system or any combinationthereof, for example, a PET-CT system. The medical imaging examinationmay be, for example, a computed tomography (CT) examination or amagnetic resonance imaging (MRI) examination or a positron emissiontomography (PET) examination or a C-arm examination or any combinationthereof, for example, a PET-CT examination. The medical imaging scan maybe, for example, a computed tomography (CT) scan or a magnetic resonanceimaging (MRI) scan or a positron emission tomography (PET) scan or aC-arm scan or any combination thereof, for example, a PET-CT scan.

According to a further embodiment of the present invention, a computerprogram including programming instructions is provided, wherein saidprogramming instructions may be loaded into the computer system of amedical imaging system, wherein said programming instructions cause saidcomputer system to carry out the method of an embodiment of the presentinvention. The computer program or computer program product may bewritten in any language readable by a medical imaging system. It may beloaded into a processing unit and may be stored on any digital storagemedium. For example, the processing unit may be or may be part of orconnected to the control unit as described herein.

A further embodiment of the present invention is directed to anon-transitory computer readable data storage medium encoded withprogramming instructions, wherein the programming instructions may beloaded into a computer system of a medical imaging system and cause saidcomputer system to carry out the method according to embodiments of thepresent invention. The data storage medium may be any digital storagemedium, for example a hard disc, a cloud, a medium connected to thecomputer system of a medical imaging system, or a portable medium suchas an SD-card or SSD-card, a USB-stick, CD-ROM etc. All features andadvantages of the method described herein are also applicable to thecomputer program and storage medium and vice versa. The method may be,for example, a computer-implemented method.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the present invention will now be described withreference to the enclosed figures, in which:

FIG. 1 shows a perspective view of a medical imaging system according toan embodiment of the present invention;

FIG. 2 shows an example of a motion model specific to the head,illustrated on two images acquired by a camera disposed above thepatient table, the images showing the head and shoulders of a subject intwo different motion states;

FIG. 3 shows a motion model tailored to breathing, illustrated on aschematic representation of a prone body;

FIG. 4 shows a flow diagram of an embodiment of a method according tothe present invention.

DETAILED DESCRIPTION

An embodiment of the present invention provides a method for controllinga medical imaging examination of a subject, wherein the medical imagingexamination comprises performing a medical imaging scan of a body regionof interest of the subject using a pre-selected scan protocol, whereinthe medical imaging examination is performed using a medical imagingsystem having a gantry, a patient table which is moveable with respectto the gantry and on which the subject is positioned, a control unit forcontrolling the medical imaging scan and having access to an imagesequence of the subject acquired by a camera, and wherein the methodcomprises the steps of receiving an image sequence of the subject fromthe camera during the medical imaging scan; receiving the currentposition and/or velocity of the patient table during the medical imagingscan; performing a motion tracking analysis of the received imagesequence to extract a motion model, wherein the motion tracking analysisand/or the motion model is tailored to the body region of interest andtakes into account the current patient table position and/or velocity;analysing the motion model to detect subject motion and, for example ifthe detected motion is above a pre-determined threshold, adapting themedical imaging examination to the detected motion and/or issuing analert to make the subject and/or an operator of the medical imagingsystem aware of the detected motion.

The method uses a camera-based approach to track and quantify patientmotion and further uses the intrinsic knowledge of the system about thescan protocol and/or the motion of the patient table to adequately adaptthe medical imaging examination to the estimated patient motion.

The medical imaging examination may be any clinical medical imagingexam, including angiography or radiation therapy planning. The medicalimaging examination may comprise one or several medical imaging scans,wherein each medical imaging scan acquires medical images from a bodyregion of interest of the subject using a pre-selected scan protocol.The scan protocol may be pre-selected by the radiologist or a doctorordering the medical imaging examination and may already specify thebody region of interest, as well as scan parameters. The scan parametersmay include the resolution, slice thickness, dose, radiation energy andwhether or not contrast agent is to be applied. Thus, the scan protocolmay be tailored to the diagnostic question (for example trauma, tumour,blood vessels, stroke), as well as the body region of interest on whichthe medical imaging scan is to be performed.

The medical imaging system has a gantry and a patient table which ismoveable with respect to the gantry and on which the subject is lying,usually in a supine position. According to an embodiment, the gantrycomprises an X-ray source and an X-ray detector, which are rotatablearound the patient table. According to an embodiment, the gantrycomprises a superconducting magnet in form of a hollow cylinder, intowhich the patient table can be inserted along an axial direction.

In some embodiments, the gantry is stationary, and the patient table ismoveable at least in axial direction (z-direction) through the gantry.However, embodiments of the present invention are also applicable tomedical imaging system with a moveable, e.g., slidable, gantry, whereinthe patient table may be stationary or may also be moveable. Gantry andpatient table are usually moveable at least in z-direction with respectto each other. The medical imaging system further comprises a controlunit for controlling the medical imaging scan, which may be part of acomputer system. The control unit has access to image sequences acquiredby a camera disposed above the subject. The motion tracking analysisaccording to embodiments of the present invention may also be performedby the control unit, or by another processing unit, which may also bepart of the computer system and which is connected via a data link tothe control unit. Thus, the processing unit may be the or part of thecontrol unit.

The camera may be fixed to the gantry and may be integrated into themedical imaging system. It may be disposed somewhere above the patienttable. It may be mounted on a separate stand or at the ceiling above thepatient table. Thus, the camera may be stationary with respect to thegantry, or alternatively with respect to the patient table. The cameramay be an optical camera, in particular a digital or video cameracapable of acquiring a time sequence of images of the patient while heis positioned on the patient table. The time resolution is preferablysufficient to capture relevant movement during the scan, for example2-120 frames per second. The camera may be a camera already integratedin state-of-the art medical imaging systems, which today is used simplyfor visual patient monitoring. According to embodiments of the presentinvention, the control unit receives not only the image sequence fromthe camera during the medical imaging scan but is also aware of orreceives the current position and/or velocity of the patient table, andoptionally also the pre-selected scan protocol.

The control unit or processing unit then performs a motion trackinganalysis of the received image sequence to extract a motion model of thebody region of interest of the subject, wherein the motion trackinganalysis and/or the motion model are tailored to the body region ofinterest and take into account the current patient table position and/orvelocity. Thereby, the motion tracking analysis may be simplified andtherefore stabilized, because based on the body region of interest andoptionally the scan protocol to be applied, an appropriate, e.g.,simplified motion model is applied. Already knowing the body region ofinterest also allows to detect the relevant body region on the images(which may have a larger field of view) beforehand.

In the next step, the motion model is analysed to detect subject motion.Preferably, the detected motion is classified as sufficient tocompromise the scan process (e.g., above a pre-determined threshold) oras non-existent or irrelevant. For example, if the threshold is crossed(or always), the medical imaging system may adapt to the motion in amanner specific to the medical imaging examination and optionally scanprotocol and/or body region.

Thus, a camera-based approach is presented to track and quantify patientmotion and to adequately adapt the medical imaging examination to theestimated patient motion. The method exploits specific informationavailable at the medical imaging system, such as the body region to bescanned and optionally the scan protocol to be applied, in order toadequately react to patient motion. The method also incorporatesavailable motion information of the patient table. Embodiments of thepresent invention, thus, provide a method for mitigating the effect ofpatient motion, in which the scan workflow is not negatively impacted byadditional devices or workflow steps to track patient motion.

The motion tracking analysis may utilise machine-learning basedalgorithms to estimate motion on the image sequence. For example,algorithms provided by Google MediaPipe (currently available underhttps://mediapipe.dev) may be used. The algorithms use e.g., neuralnetworks, to extract the position of pre-determined objects on eachimage. Thereby, motion can be estimated directly from the RGB imagedata, or in the case of a three-dimensional (3D) camera acquiring imageswith depth information, also form the depth data. In low-end medicalimaging systems, where only two-dimensional (2D) cameras are available,the motion tracking analysis may include deriving the motion from the 2Dimage sequences using a state-of-the art algorithms. By taking intoaccount the current patient table position and/or velocity, the motionmay be corrected for movements of the medical imaging system patienttable, that are explicitly known within the control unit. One correctionapproach is to subtract the table motion from the camera-estimatedoverall motion. This ensures that only patient motion relative to thetable is captured by the camera-based motion estimates.

According to an embodiment, the motion tracking analysis uses a motionmodel which is specific to the selected scan protocol and/or the bodyregion of interest. In some embodiments, the selected scan protocolalready comprises the relevant body region, wherein the body region ofinterest may for example be head, thorax, a limb or part of a limb, hip,neck, shoulder, or any other body part which may be covered by a medicalimaging scan. The motion model may be tailored to the shape, thefeatures and/or the kind of motion that may occur in the specific bodyregion. In particular, the motion model may consider the joints and themovement they allow. For example, the head may, in a firstapproximation, be taken as a rigid body, i.e., it can rotate andpossibly translate, but the skull cannot deform within itself. In asecond approximation, movements of the jaw and throat, such asswallowing, may be incorporated into the model. Motion models of thelimbs may incorporate the possible movement at the joints, whereas amotion model of the thorax will include breathing motion and optionallythe heartbeat. Thus, the motion tracking analysis will specifically lookout for motion which fits the motion model specific to the body regionof interest to be scanned.

The default/general motion model may be a dense, elastic motion fieldcapturing the motion at each image position.

When the motion model is specific to the body region of interest, themotion tracking analysis may comprise detecting and tracking landmarksspecific to the body region of interest in the image sequence, applyinga filter algorithm to the tracked landmarks to compensate inaccuratedetections in one or several of the images of the sequence, inparticular a Kalman filter; correcting the tracked landmarks by theposition and/or velocity of the patient table; and estimating the motionmodel based on the filtered and corrected landmarks.

The landmarks can be detected for example by an algorithm based on atrained neural network. Thus, an appropriate number of landmarks (e.g.,6-300, preferably 40-150) may be pre-defined for each specific bodyregion, wherein the landmarks designate characteristic portions of thebody surface. If the body region is the head, the landmarks may befacial landmarks, which may be used to determine the position of theeyes, nose, and mouth.

Since the landmarks are detected in each image of the sequenceindependently of each other, errors in the detection may lead to abruptchanges from on image to the next, leading to instability. Therefore, afilter algorithm may be applied to the tracked landmarks to compensateinaccurate detections in one or several of the images. In oneembodiment, this may be a Kalman filter, as described for example in G.Welch and G. Bishop “An Introduction to the Kalman Filter”, Sep. 17,1997. A Kalman filter is an algorithm that uses a series of measurementsobserved over time (here: the positions of the tracked landmarks)containing statistical noise and other inaccuracies, to produceestimates of unknown valuables (here: the positions of tracked landmarkson later/future images in the series) that tend to be more accurate thanthose based on a single measurement alone. By using a Kalman filter, themotion of the tracked landmarks can be estimated with higher certaintyand stability. An alternative algorithm is the Sparse Optical Flowalgorithm, for example, as described in J. Barron, D. Fleet and S. S.Beauchemin “Performance of Optical Flow Techniques”, InternationalJournal of Computer vision 12, 43-77 (1994). This technique may be usedto approximate the 2D motion field, i.e., the projection of 3Dvelocities onto the imaging surface, from the image intensity of theimage sequence.

Since the subject motion is being tracked during a medical imaging scan,table movement is expected. To ensure that only the movement of the bodyregion of interest, for example the head, is detected, the positions ofthe tracked landmarks may be corrected according to the patient tablemovement. These table movements (position and/or velocity including thedirection) are explicitly known within the medical imaging system, e.g.,in the control unit. Thus, based on the filtered and correctedlandmarks, a motion model specific to the body region can be estimated.In an embodiment, the motion vectors of the landmarks constitute themotion model.

According to an embodiment, the motion tracking analysis furthercomprises estimating rotation and translation vectors on the basis ofthe positions of the landmarks on each image of the sequence and thecamera parameters, determining the orientation and movement of the bodyregion of interest, in particular the head, based on the detectedlandmarks and the rotation and translation vectors. From the position ofthe landmarks and the known intrinsic parameters of the camera, inparticular the camera's position and orientation with respect to thepatient table, rotation and translation vectors can be estimated. Thesetranslation and rotation vectors may for example apply to a body regionwhich may be assumed to be a rigid body, such as the head. In this case,only 6 degrees of freedom (three translation vectors and the three Eulerangles) need to be estimated for each time point.

For this purpose, a direct linear transform solution with the knownintrinsic parameters of the camera could be applied. In this process,each landmark of the body of interest in the world coordinate system isprojected onto the image plane to consider the orientation and positionof the body from an image sequence to the camera. To minimize projectionerrors, a Levenberg-Marquart optimisation could be applied toiteratively adjust the rotation and translation vectors. Furthermore,the resulting vectors and the intrinsic parameters of the camera may beused to calculate the Euler angles. Consequently, the orientation andmovement of the head may be checked based on the determined faciallandmarks, vectors and angles.

According to an embodiment, the method comprises a step of correctingthe motion model or the motion vector field by the patient tablevelocity. This may be done by correcting the motion model, in particularthe position for the landmarks and motion vectors, by estimating thetranslation using the current position and/or velocity of the patienttable. Thereby, the table motion in the images in the images may becompensated by shifting the image content by the table motion. Further,the control unit may identify the current patient table position, andonly once the table position is close to the target position for theexamination, the motion tracking analysis is started. In anotherembodiment, the threshold for motion recognition may be corrected by thepatient table velocity.

According to an embodiment, the motion tracking analysis is started onlyonce the patient table has reached a target position for theexamination. Usually, the patient will lie down on the patient tablewhile it is disposed outside the gantry, and then the patient table willbe shifted at least in z-direction into the gantry, to a target positionfor this examination, e.g., such that the body region of interest isinside the gantry. By starting the motion tracking approach only oncethe patient table is at the target position, the calculation effort forcorrecting fast table motion may be reduced.

In the event that the body region is the thorax, the motion trackinganalysis may comprise the extraction of a one-dimensional (1D) model ofupwards and downwards motion of the thorax from the image sequenceacquired by a three-dimensional camera. This implies that depthinformation is available, and in this case the upward/downward motionmay provide an adequate model of breathing. For example, the motiontracking analysis may comprise a step of averaging the depth (i.e.,distance from the camera) of the chest over a pre-defined area on eachimage of the sequence, and optionally using a Kalman filter to predictthe further breathing motion. Since the breathing motion is cyclic,extrapolation of the movement is possible.

The motion tracking analysis may comprise a step of applying a densemotion tracking approach to the sequence of images to estimate a motionvector field, in particular by using an optical flow technique. Thisapproach is advantageous in particular in case only 2-D camera motiontracking is available. This may be followed by correcting the motionvector field by the patient table velocity. From the motion field, thebreathing motion may be extracted as follows:

According to an embodiment, the motion vector field is calculated firstin a coarse resolution, followed by a calculation by one or severalfiner resolutions. In other words, the analysis may be performed in amulti-resolution fashion to obtain a global breathing model at a coarselevel, but and detect further movements at the finer resolutions. In anexample, the image sequence may have a resolution of 640×1080 pixels.However, in the first step, it is sampled to a much lower resolution, inorder to estimate motion on a large scale first. This has the advantagethat aliasing is suppressed. When the main movements have beenidentified, the analysis is repeated on a finer resolution, to furtherdifferentiate detected motion.

According to an embodiment, the motion tracking analysis may furthercomprise the steps of analysing the orientation of the motion vectorfield for detecting inward and outward motion, in particular bycalculating the divergence of the motion vector field, and on this basisestimating a motion model of breathing motion.

This is based on the insight that inspiration and expiration can bedifferentiated by analysing the orientation of the motion vectors: atthe sides of the body, inspiration, i.e., an expansion of the chest, ischaracterized by motion vectors pointing towards the boundaries of theimage. During expiration, i.e., contraction of the chest, the motionvectors point towards the centre. Mathematically, this may becharacterised by the divergence of the vector field, a positive valueindicates an expansion of the chest (inspiration), a negative valueindicating expiration.

Further, a secondary breathing motion in z-direction may be observed inthe waist region or the shoulder region. For the shoulders, inspirationleads to a shift towards the head, whereas expiration leads to amovement towards the feet. At the waist, the motion may be upwards ordownwards for inspiration, depending on whether chest or abdominalbreathing is dominant. Nevertheless, the movement in z-direction at thewaist may be valuable to support the detection of breathing and todifferentiate between chest and abdominal breathing if the generalphases of inspiration/expiration are detected from the body sides or theshoulders. The magnitude of the motion vector field describes the amountof breathing motion. The above-described multi-resolution analysis maybe used to be able to differentiate between abdominal and chestbreathing in the finer resolutions.

Based on the detected motion, in particular whether the motion crosses athreshold, the medical imaging system may react and adapt the medicalimaging examination in on or more ways.

According to an embodiment, the medical imaging system may issue analert to the subject and/or the operator. For example, the operator,i.e., a technician or radiological assistant, may receive a visual oracoustic warning. The visual warning can be realized as a colour overlayon the live image shown on the scanner tablet. The alert may include thekind of detected motion, and suggestions for action. For example, tore-position the patient, or to instruct the patient to counteract themovement. Alternatively, the subject may be made aware of the motionthrough a visual or acoustic warning. According to an embodiment, thealert issued to the subject may comprise the kind of motion and/or asuggestion for correcting the motion. For example, the alert may includea visual or acoustic sign to catch the subject's attention. Afterwards,one or more of the images acquired by the camera may be displayed to thesubject on a screen, including arrows to indicate how the patient shouldmove in order to correct the inadvertent motion. For example, there maybe an arrow or an acoustic sign, asking him to turn his head back to thecentre, when he/she before turned the head to one side.

According to another embodiment, adapting the medical imagingexamination may comprise re-acquiring the medical imaging data whichwere compromised by the detected motion. The medical imaging data maybe, for example, computed tomography data or magnetic resonance imagingdata.

For example, the patient table may stop or move backwards to allow themedical imaging system to scan the affected portions again. This may benecessary for example when coughing is detected, which is possible usingthe inventive technique. In prior art techniques, only a respiratorysurrogate (i.e., a simplified 1D signal) was detected via the chestbelt, and this could not detect complex movement like coughing. Bydetecting couching in the camera-based inventive approach, re-scanningof certain z-positions may be triggered when necessary.

According to a further embodiment, adapting the medical imagingexamination may comprise performing a motion-compensated imagereconstruction of the medical imaging data (also referred to asmotion-compensated medical image reconstruction), for example amotion-compensated filtered-back projection. In other words, thecamera-based motion estimation may be used as input information forstate-of-the-art motion-compensated reconstruction algorithms, like thealgorithm by Dirk Schafer mentioned above, to correct the reconstructionfor the estimated motion. The medical image reconstruction may be, forexample, a computed tomography image reconstruction or a magneticresonance image reconstruction.

According to an embodiment, the medical imaging examination is acomputed tomography examination (also referred to as a CT examination),the medical imaging scan is a computed tomography scan (also referred toas a CT scan), and the medical imaging system is a computed tomographysystem (also referred to as a CT system).

In particular, a method for controlling a CT examination of a subject isdisclosed herewith, wherein the CT examination comprises performing a CTscan of a body region of interest of the subject using a pre-selectedscan protocol,

wherein the CT examination is performed using a CT system having agantry, a patient table which is moveable with respect to the gantry andon which the subject is positioned, a control unit for controlling theCT scan and having access to an image sequence of the subject acquiredby a camera, and wherein the method comprises the steps of(a) receiving an image sequence of the subject from the camera duringthe CT scan;(b) receiving the current position and/or velocity of the patient tableduring the CT scan;(c) performing a motion tracking analysis of the received image sequenceto extract a motion model, wherein the motion tracking analysis and/orthe motion model is tailored to the body region of interest and takesinto account the current patient table position and/or velocity;(d) analysing the motion model to detect subject motion and, for exampleif the detected motion is above a pre-determined threshold, adapting theCT examination to the detected motion and/or issuing an alert to makethe subject and/or an operator of the CT system aware of the detectedmotion.

According to an embodiment, the medical imaging examination is amagnetic resonance imaging examination (also referred to as an MRIexamination), the medical imaging scan is a magnetic resonance imagingscan (also referred to as an MRI scan), and the medical imaging systemis a magnetic resonance imaging system (also referred to as an MRIsystem).

Embodiments of the present invention are further directed to a medicalimaging system comprising a gantry, a patient table which is moveablewith respect to the gantry, a camera disposed above the patient table ina known position and orientation with respect to the gantry, wherein thecamera is adapted to acquire an image series of a subject positioned onthe patient table, and a control unit for controlling a medical imagingscan. The control unit is adapted to receive an image sequence of thesubject from the camera during the medical imaging scan, and the currentposition and/or velocity of the patient table during the medical imagingscan. The control unit is further adapted for performing a motiontracking analysis of the received image sequence to extract a motionmodel, wherein the motion tracking analysis and/or the motion model istailored to the body region of interest and takes into account thecurrent patient table position and/or velocity; and the control unit isfurther adapted for analysing the motion model to detect subject motionand, for example if the detected motion is above a pre-determinedthreshold, for adapting the medical imaging examination to the detectedmotion and/or for issuing an alert to make the subject and/or anoperator of the medical imaging system aware of the detected motion.

The medical imaging system is adapted for performing the methodaccording to embodiments of the present invention. All features andadvantages described with respect to the method are also applicable tothe medical imaging system and vice versa. The method may be (at leastpartly) carried out by a control unit, which is part of the medicalimaging system, and which receives the image sequence, performs themotion tracking analysis, and may adapt the medical imaging examinationto react to the detected motion.

According to an embodiment, the camera is a video camera or digitalcamera adapted to acquire 2-D. The camera may be integrated into thegantry. Thereby, the position and other intrinsic camera parameters,such as the field-of-view, the imaging angle with respect to the patienttable, the resolution, etc. are automatically known to the medicalimaging system, in particular the control unit.

According to an alternative embodiment, the camera inside is a 3D cameraadapted to acquire images including depth information of the subject.Such 3D cameras may for example include two lenses in order to capturethe body region of interest in two angles, and thereby extractcontour/depth information.

The medical imaging system may be, for example, a computed tomography(CT) system or a magnetic resonance imaging (MRI) system or a positronemission tomography (PET) system or a C-arm system or any combinationthereof, for example, a PET-CT system. The medical imaging examinationmay be, for example, a computed tomography (CT) examination or amagnetic resonance imaging (MRI) examination or a positron emissiontomography (PET) examination or a C-arm examination or any combinationthereof, for example, a PET-CT examination. The medical imaging scan maybe, for example, a computed tomography (CT) scan or a magnetic resonanceimaging (MRI) scan or a positron emission tomography (PET) scan or aC-arm scan or any combination thereof, for example, a PET-CT scan.

According to a further embodiment of the present invention, a computerprogram including programming instructions is provided, wherein saidprogramming instructions may be loaded into the computer system of amedical imaging system, wherein said programming instructions cause saidcomputer system to carry out the method of an embodiment of the presentinvention. The computer program or computer program product may bewritten in any language readable by a medical imaging system. It may beloaded into a processing unit and may be stored on any digital storagemedium. For example, the processing unit may be or may be part of orconnected to the control unit as described herein.

A further embodiment of the present invention is directed to anon-transitory computer readable data storage medium encoded withprogramming instructions, wherein the programming instructions may beloaded into a computer system of a medical imaging system and cause saidcomputer system to carry out the method according to embodiments of thepresent invention. The data storage medium may be any digital storagemedium, for example a hard disc, a cloud, a medium connected to thecomputer system of a medical imaging system, or a portable medium suchas an SD-card or SSD-card, a USB-stick, CD-ROM etc. All features andadvantages of the method described herein are also applicable to thecomputer program and storage medium and vice versa. The method may be,for example, a computer-implemented method.

FIG. 1 shows a medical imaging system according to an embodiment of thepresent invention, which is adapted to carry out the inventive method.The medical imaging system 1 comprises a ring-shaped gantry 2. A patienttable 3 is disposed on a foot 4 and can be moved in z-direction throughthe gantry via an actuator 6, which may include and electric motor, andwhich is connected by a data link 7 with control unit 8. The controlunit 8 is part of computer system 10, which may further comprise aprocessing unit 12 and a data storage 14, such as a hard disc. Acomputer program product stored on CD-ROM 15 may be loaded into thecomputer system 10. The computer system 10 may have the user interface,for example in the shape of a screen 16 and a keyboard 19. The controlunit 8 further controls the operation of the medical imaging system 1,in particular the gantry 2. It is also connected via a data link 17 witha camera 18 which is disposed on the housing of the gantry above thepatient table 3. The control unit 8 may further be connected with atablet 20, on which the images taken by the camera 18 may be visualized,as well as a user input device 22, which may have the shape of a remotecontrol. The data links 7 and 17 may be cable-bound, but also may bewireless, for example by Bluetooth, WIFI or other data connections. Thecontrol unit 8 and/or the computer system 10, or the processing unit 12may be situated remote from the medical imaging system, so the that thedata links 7 and 17 are via one or more telecommunication systems orlinks, or via the internet.

FIG. 2 illustrates the motion tracking analysis tailored to the head asthe body region of interest. FIG. 2 shows two images, 30 on the left and32 on the right, of a head 34 of a subject 36 lying on the patient table3 beneath the camera 18. On each image acquired by the camera, a numberof pre-determined facial landmarks 38 is detected, shown as dots 38. Thefacial landmarks outline the contour of the head, as well as thedistinctive features of the face such as eyes, nose, and mouth. If thepatient table 3 is moving, the position of the landmarks may becorrected according to the known movement of the patient table 3, whichis recorded by actuator 6 and forwarded to control unit 8. From thefacial landmarks 38, and taking into account the known intrinsicparameters of the camera, the motion tracking analysis with the directlinear transform solution followed by a Levenberg-Marquart optimizationwill calculate the axes of the head on each image, for example thelongitudinal axis x, the front-to-back axis y, and the left-to-rightaxis z. These axes are illustrated by cube 40 on each image.

For thorax scans, especially if only 2D camera motion tracking isavailable, a general dense motion tracking approach such as Optical Flowis applied to firstly estimate a motion vector field. From this motionfield, the breathing motion is extracted as follows: the estimatedmotion vectors, as illustrated in FIG. 3 , are first corrected by theknown table motion. Now looking at FIG. 3 , the motion model isillustrated on a schematic top view of a patient 36, in particular hisshoulders 42, chest 44 and waist/belt 46. During inspiration, i.e.,expansion of the chest 44, the sides of the body move outwards asillustrated by motion vectors 50. The shoulders move upwards, seevectors 52. During expiration, the shoulders move downward, see vectors54, and the chest inwards, see motion vectors 56. Mathematically, thiscan be shown by calculating the divergence of the vector field, withexpansion of the chest having a positive divergence, expiration beingcharacterized by a negative divergence.

In order to distinguish chest and abdominal breathing, the motion at thewaist or belt 46 may be further analysed: chest breathing ischaracterized by upwards movements 58, abdominal breathing by downwardmotion 59. Thus, the main value of analysing the motion fields at thewaist is to support the detection of breathing, and to differentiatebetween the chest and abdominal breathing. The motion vector field ispreferably extracted from the colour image of the subject and may beperformed in a multi-resolution fashion to obtain a global breathingmodel at a course level, but still be able to differentiate for examplebetween abdominal and chest breathing on the finer scales.

FIG. 4 illustrates an embodiment of the method of the present invention.In step 60, the patient is positioned onto the patient table 3, and themedical imaging examination is begun. And operator will select ascan-protocol and a body region of interest. In the next step 62, thecamera will start acquiring images and send the image sequence of thesubject to the control unit 8. When the patient table 3 begins to moveby actuator 6, also the current position and motion of the patient tablewill be sent to the control unit 8 in step 64. The control unit 8 or theprocessing unit 12 will perform the motion tracking analysis 66 of thereceived image sequence and extract the specific motion model, which istailored to the specific body region. At the same time, the medicalimaging scan 68 is going on, in particular the patient table 3 is slowlymoving through the gantry 2 while medical imaging data is acquired. Instep 70, the motion model is analysed to detect subject motion andpossibly adapt the medical imaging examination to the detected motion,as illustrated by arrow 72, by which a part of the scan 68 may berepeated at a certain z-position in which motion occurred. The steps 64,66 and 70 are generally ongoing during the scan 68, at least steps 62and 64. Preferably also the motion tracking analysis 66 and the analysisof the motion model 70 is occurring in real time, because this allowsthe medical imaging system to issue an alert to make the subject or theoperator aware of the detected motion, as indicated at 74. Such an alertmay for example be a sound signal and/or a visual indication of how thesubject should move back into his initial position.

At 76, the medical imaging scan 68 is completed, and a reconstruction ofthe images may be performed, optionally taking into account thecalculated motion model.

The drawings are to be regarded as being schematic representations andelements illustrated in the drawings are not necessarily shown to scale.Rather, the various elements are represented such that their functionand general purpose become apparent to a person skilled in the art. Anyconnection or coupling between functional blocks, devices, components,or other physical or functional units shown in the drawings or describedherein may also be implemented by an indirect connection or coupling. Acoupling between components may also be established over a wirelessconnection. Functional blocks may be implemented in hardware, firmware,software, or a combination thereof.

It will be understood that, although the terms first, second, etc. maybe used herein to describe various elements, components, regions,layers, and/or sections, these elements, components, regions, layers,and/or sections, should not be limited by these terms. These terms areonly used to distinguish one element from another. For example, a firstelement could be termed a second element, and, similarly, a secondelement could be termed a first element, without departing from thescope of example embodiments. As used herein, the term “and/or,”includes any and all combinations of one or more of the associatedlisted items. The phrase “at least one of” has the same meaning as“and/or”.

Spatially relative terms, such as “beneath,” “below,” “lower,” “under,”“above,” “upper,” and the like, may be used herein for ease ofdescription to describe one element or feature's relationship to anotherelement(s) or feature(s) as illustrated in the figures. It will beunderstood that the spatially relative terms are intended to encompassdifferent orientations of the device in use or operation in addition tothe orientation depicted in the figures. For example, if the device inthe figures is turned over, elements described as “below,” “beneath,” or“under,” other elements or features would then be oriented “above” theother elements or features. Thus, the example terms “below” and “under”may encompass both an orientation of above and below. The device may beotherwise oriented (rotated 90 degrees or at other orientations) and thespatially relative descriptors used herein interpreted accordingly. Inaddition, when an element is referred to as being “between” twoelements, the element may be the only element between the two elements,or one or more other intervening elements may be present.

Spatial and functional relationships between elements (for example,between modules) are described using various terms, including “on,”“connected,” “engaged,” “interfaced,” and “coupled.” Unless explicitlydescribed as being “direct,” when a relationship between first andsecond elements is described in the disclosure, that relationshipencompasses a direct relationship where no other intervening elementsare present between the first and second elements, and also an indirectrelationship where one or more intervening elements are present (eitherspatially or functionally) between the first and second elements. Incontrast, when an element is referred to as being “directly” on,connected, engaged, interfaced, or coupled to another element, there areno intervening elements present. Other words used to describe therelationship between elements should be interpreted in a like fashion(e.g., “between,” versus “directly between,” “adjacent,” versus“directly adjacent,” etc.).

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of exampleembodiments. As used herein, the singular forms “a,” “an,” and “the,”are intended to include the plural forms as well, unless the contextclearly indicates otherwise. As used herein, the terms “and/or” and “atleast one of” include any and all combinations of one or more of theassociated listed items. It will be further understood that the terms“comprises,” “comprising,” “includes,” and/or “including,” when usedherein, specify the presence of stated features, integers, steps,operations, elements, and/or components, but do not preclude thepresence or addition of one or more other features, integers, steps,operations, elements, components, and/or groups thereof. As used herein,the term “and/or” includes any and all combinations of one or more ofthe associated listed items. Expressions such as “at least one of,” whenpreceding a list of elements, modify the entire list of elements and donot modify the individual elements of the list. Also, the term “example”is intended to refer to an example or illustration.

It should also be noted that in some alternative implementations, thefunctions/acts noted may occur out of the order noted in the figures.For example, two figures shown in succession may in fact be executedsubstantially concurrently or may sometimes be executed in the reverseorder, depending upon the functionality/acts involved.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which example embodiments belong. Itwill be further understood that terms, e.g., those defined in commonlyused dictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the relevant art andwill not be interpreted in an idealized or overly formal sense unlessexpressly so defined herein.

It is noted that some example embodiments may be described withreference to acts and symbolic representations of operations (e.g., inthe form of flow charts, flow diagrams, data flow diagrams, structurediagrams, block diagrams, etc.) that may be implemented in conjunctionwith units and/or devices discussed above. Although discussed in aparticularly manner, a function or operation specified in a specificblock may be performed differently from the flow specified in aflowchart, flow diagram, etc. For example, functions or operationsillustrated as being performed serially in two consecutive blocks mayactually be performed simultaneously, or in some cases be performed inreverse order. Although the flowcharts describe the operations assequential processes, many of the operations may be performed inparallel, concurrently or simultaneously. In addition, the order ofoperations may be re-arranged. The processes may be terminated whentheir operations are completed, but may also have additional steps notincluded in the figure. The processes may correspond to methods,functions, procedures, subroutines, subprograms, etc.

Specific structural and functional details disclosed herein are merelyrepresentative for purposes of describing example embodiments. Thepresent invention may, however, be embodied in many alternate forms andshould not be construed as limited to only the embodiments set forthherein.

Units and/or devices according to one or more example embodiments may beimplemented using hardware, software, and/or a combination thereof. Forexample, hardware devices may be implemented using processing circuitysuch as, but not limited to, a processor, Central Processing Unit (CPU),a controller, an arithmetic logic unit (ALU), a digital signalprocessor, a microcomputer, a field programmable gate array (FPGA), aSystem-on-Chip (SoC), a programmable logic unit, a microprocessor, orany other device capable of responding to and executing instructions ina defined manner. Portions of the example embodiments and correspondingdetailed description may be presented in terms of software, oralgorithms and symbolic representations of operation on data bits withina computer memory. These descriptions and representations are the onesby which those of ordinary skill in the art effectively convey thesubstance of their work to others of ordinary skill in the art. Analgorithm, as the term is used here, and as it is used generally, isconceived to be a self-consistent sequence of steps leading to a desiredresult. The steps are those requiring physical manipulations of physicalquantities. Usually, though not necessarily, these quantities take theform of optical, electrical, or magnetic signals capable of beingstored, transferred, combined, compared, and otherwise manipulated. Ithas proven convenient at times, principally for reasons of common usage,to refer to these signals as bits, values, elements, symbols,characters, terms, numbers, or the like.

It should be borne in mind that all of these and similar terms are to beassociated with the appropriate physical quantities and are merelyconvenient labels applied to these quantities. Unless specificallystated otherwise, or as is apparent from the discussion, terms such as“processing” or “computing” or “calculating” or “determining” of“displaying” or the like, refer to the action and processes of acomputer system, or similar electronic computing device/hardware, thatmanipulates and transforms data represented as physical, electronicquantities within the computer system's registers and memories intoother data similarly represented as physical quantities within thecomputer system memories or registers or other such information storage,transmission or display devices.

In this application, including the definitions below, the term ‘module’or the term ‘controller’ may be replaced with the term ‘circuit.’ Theterm ‘module’ may refer to, be part of, or include processor hardware(shared, dedicated, or group) that executes code and memory hardware(shared, dedicated, or group) that stores code executed by the processorhardware.

The module may include one or more interface circuits. In some examples,the interface circuits may include wired or wireless interfaces that areconnected to a local area network (LAN), the Internet, a wide areanetwork (WAN), or combinations thereof. The functionality of any givenmodule of the present disclosure may be distributed among multiplemodules that are connected via interface circuits. For example, multiplemodules may allow load balancing. In a further example, a server (alsoknown as remote, or cloud) module may accomplish some functionality onbehalf of a client module.

Software may include a computer program, program code, instructions, orsome combination thereof, for independently or collectively instructingor configuring a hardware device to operate as desired. The computerprogram and/or program code may include program or computer-readableinstructions, software components, software modules, data files, datastructures, and/or the like, capable of being implemented by one or morehardware devices, such as one or more of the hardware devices mentionedabove. Examples of program code include both machine code produced by acompiler and higher level program code that is executed using aninterpreter.

For example, when a hardware device is a computer processing device(e.g., a processor, Central Processing Unit (CPU), a controller, anarithmetic logic unit (ALU), a digital signal processor, amicrocomputer, a microprocessor, etc.), the computer processing devicemay be configured to carry out program code by performing arithmetical,logical, and input/output operations, according to the program code.Once the program code is loaded into a computer processing device, thecomputer processing device may be programmed to perform the programcode, thereby transforming the computer processing device into a specialpurpose computer processing device. In a more specific example, when theprogram code is loaded into a processor, the processor becomesprogrammed to perform the program code and operations correspondingthereto, thereby transforming the processor into a special purposeprocessor.

Software and/or data may be embodied permanently or temporarily in anytype of machine, component, physical or virtual equipment, or computerstorage medium or device, capable of providing instructions or data to,or being interpreted by, a hardware device. The software also may bedistributed over network coupled computer systems so that the softwareis stored and executed in a distributed fashion. In particular, forexample, software and data may be stored by one or more computerreadable recording mediums, including the tangible or non-transitorycomputer-readable storage media discussed herein.

Even further, any of the disclosed methods may be embodied in the formof a program or software. The program or software may be stored on anon-transitory computer readable medium and is adapted to perform anyone of the aforementioned methods when run on a computer device (adevice including a processor). Thus, the non-transitory, tangiblecomputer readable medium, is adapted to store information and is adaptedto interact with a data processing facility or computer device toexecute the program of any of the above mentioned embodiments and/or toperform the method of any of the above mentioned embodiments.

Example embodiments may be described with reference to acts and symbolicrepresentations of operations (e.g., in the form of flow charts, flowdiagrams, data flow diagrams, structure diagrams, block diagrams, etc.)that may be implemented in conjunction with units and/or devicesdiscussed in more detail below. Although discussed in a particularlymanner, a function or operation specified in a specific block may beperformed differently from the flow specified in a flowchart, flowdiagram, etc. For example, functions or operations illustrated as beingperformed serially in two consecutive blocks may actually be performedsimultaneously, or in some cases be performed in reverse order.

According to one or more example embodiments, computer processingdevices may be described as including various functional units thatperform various operations and/or functions to increase the clarity ofthe description. However, computer processing devices are not intendedto be limited to these functional units. For example, in one or moreexample embodiments, the various operations and/or functions of thefunctional units may be performed by other ones of the functional units.Further, the computer processing devices may perform the operationsand/or functions of the various functional units without sub-dividingthe operations and/or functions of the computer processing units intothese various functional units.

Units and/or devices according to one or more example embodiments mayalso include one or more storage devices. The one or more storagedevices may be tangible or non-transitory computer-readable storagemedia, such as random access memory (RAM), read only memory (ROM), apermanent mass storage device (such as a disk drive), solid state (e.g.,NAND flash) device, and/or any other like data storage mechanism capableof storing and recording data. The one or more storage devices may beconfigured to store computer programs, program code, instructions, orsome combination thereof, for one or more operating systems and/or forimplementing the example embodiments described herein. The computerprograms, program code, instructions, or some combination thereof, mayalso be loaded from a separate computer readable storage medium into theone or more storage devices and/or one or more computer processingdevices using a drive mechanism. Such separate computer readable storagemedium may include a Universal Serial Bus (USB) flash drive, a memorystick, a Blu-ray/DVD/CD-ROM drive, a memory card, and/or other likecomputer readable storage media. The computer programs, program code,instructions, or some combination thereof, may be loaded into the one ormore storage devices and/or the one or more computer processing devicesfrom a remote data storage device via a network interface, rather thanvia a local computer readable storage medium. Additionally, the computerprograms, program code, instructions, or some combination thereof, maybe loaded into the one or more storage devices and/or the one or moreprocessors from a remote computing system that is configured to transferand/or distribute the computer programs, program code, instructions, orsome combination thereof, over a network. The remote computing systemmay transfer and/or distribute the computer programs, program code,instructions, or some combination thereof, via a wired interface, an airinterface, and/or any other like medium.

The one or more hardware devices, the one or more storage devices,and/or the computer programs, program code, instructions, or somecombination thereof, may be specially designed and constructed for thepurposes of the example embodiments, or they may be known devices thatare altered and/or modified for the purposes of example embodiments.

A hardware device, such as a computer processing device, may run anoperating system (OS) and one or more software applications that run onthe OS. The computer processing device also may access, store,manipulate, process, and create data in response to execution of thesoftware. For simplicity, one or more example embodiments may beexemplified as a computer processing device or processor; however, oneskilled in the art will appreciate that a hardware device may includemultiple processing elements or processors and multiple types ofprocessing elements or processors. For example, a hardware device mayinclude multiple processors or a processor and a controller. Inaddition, other processing configurations are possible, such as parallelprocessors.

The computer programs include processor-executable instructions that arestored on at least one non-transitory computer-readable medium (memory).The computer programs may also include or rely on stored data. Thecomputer programs may encompass a basic input/output system (BIOS) thatinteracts with hardware of the special purpose computer, device driversthat interact with particular devices of the special purpose computer,one or more operating systems, user applications, background services,background applications, etc. As such, the one or more processors may beconfigured to execute the processor executable instructions.

The computer programs may include: (i) descriptive text to be parsed,such as HTML (hypertext markup language) or XML (extensible markuplanguage), (ii) assembly code, (iii) object code generated from sourcecode by a compiler, (iv) source code for execution by an interpreter,(v) source code for compilation and execution by a just-in-timecompiler, etc. As examples only, source code may be written using syntaxfrom languages including C, C++, C#, Objective-C, Haskell, Go, SQL, R,Lisp, Java®, Fortran, Perl, Pascal, Curl, OCaml, Javascript®, HTML5,Ada, ASP (active server pages), PHP, Scala, Eiffel, Smalltalk, Erlang,Ruby, Flash®, Visual Basic®, Lua, and Python®.

Further, at least one example embodiment relates to the non-transitorycomputer-readable storage medium including electronically readablecontrol information (processor executable instructions) stored thereon,configured in such that when the storage medium is used in a controllerof a device, at least one embodiment of the method may be carried out.

The computer readable medium or storage medium may be a built-in mediuminstalled inside a computer device main body or a removable mediumarranged so that it can be separated from the computer device main body.The term computer-readable medium, as used herein, does not encompasstransitory electrical or electromagnetic signals propagating through amedium (such as on a carrier wave); the term computer-readable medium istherefore considered tangible and non-transitory. Non-limiting examplesof the non-transitory computer-readable medium include, but are notlimited to, rewriteable non-volatile memory devices (including, forexample flash memory devices, erasable programmable read-only memorydevices, or a mask read-only memory devices); volatile memory devices(including, for example static random access memory devices or a dynamicrandom access memory devices); magnetic storage media (including, forexample an analog or digital magnetic tape or a hard disk drive); andoptical storage media (including, for example a CD, a DVD, or a Blu-rayDisc). Examples of the media with a built-in rewriteable non-volatilememory, include but are not limited to memory cards; and media with abuilt-in ROM, including but not limited to ROM cassettes; etc.Furthermore, various information regarding stored images, for example,property information, may be stored in any other form, or it may beprovided in other ways.

The term code, as used above, may include software, firmware, and/ormicrocode, and may refer to programs, routines, functions, classes, datastructures, and/or objects. Shared processor hardware encompasses asingle microprocessor that executes some or all code from multiplemodules. Group processor hardware encompasses a microprocessor that, incombination with additional microprocessors, executes some or all codefrom one or more modules. References to multiple microprocessorsencompass multiple microprocessors on discrete dies, multiplemicroprocessors on a single die, multiple cores of a singlemicroprocessor, multiple threads of a single microprocessor, or acombination of the above.

Shared memory hardware encompasses a single memory device that storessome or all code from multiple modules. Group memory hardwareencompasses a memory device that, in combination with other memorydevices, stores some or all code from one or more modules.

The term memory hardware is a subset of the term computer-readablemedium. The term computer-readable medium, as used herein, does notencompass transitory electrical or electromagnetic signals propagatingthrough a medium (such as on a carrier wave); the term computer-readablemedium is therefore considered tangible and non-transitory. Non-limitingexamples of the non-transitory computer-readable medium include, but arenot limited to, rewriteable non-volatile memory devices (including, forexample flash memory devices, erasable programmable read-only memorydevices, or a mask read-only memory devices); volatile memory devices(including, for example static random access memory devices or a dynamicrandom access memory devices); magnetic storage media (including, forexample an analog or digital magnetic tape or a hard disk drive); andoptical storage media (including, for example a CD, a DVD, or a Blu-rayDisc). Examples of the media with a built-in rewriteable non-volatilememory, include but are not limited to memory cards; and media with abuilt-in ROM, including but not limited to ROM cassettes; etc.Furthermore, various information regarding stored images, for example,property information, may be stored in any other form, or it may beprovided in other ways.

The apparatuses and methods described in this application may bepartially or fully implemented by a special purpose computer created byconfiguring a general purpose computer to execute one or more particularfunctions embodied in computer programs. The functional blocks andflowchart elements described above serve as software specifications,which can be translated into the computer programs by the routine workof a skilled technician or programmer.

Although described with reference to specific examples and drawings,modifications, additions and substitutions of example embodiments may bevariously made according to the description by those of ordinary skillin the art. For example, the described techniques may be performed in anorder different with that of the methods described, and/or componentssuch as the described system, architecture, devices, circuit, and thelike, may be connected or combined to be different from theabove-described methods, or results may be appropriately achieved byother components or equivalents.

Although the present invention has been disclosed in the form ofembodiments and variations thereon, it will be understood that numerousadditional modifications and variations could be made thereto withoutdeparting from the scope of the present invention.

What is claimed is:
 1. A method for controlling a medical imagingexamination of a subject, the medical imaging examination includingperforming a medical imaging scan of a body region of interest of thesubject using a scan protocol, the medical imaging examination beingperformed using a medical imaging system having a gantry, a patienttable configured to move with respect to the gantry and on which thesubject is positioned, and a control unit configured to control themedical imaging scan and access an image sequence of the subjectacquired by a camera, the method comprising: receiving an image sequenceof the subject from the camera during the medical imaging scan;receiving at least one of a current position or a current velocity ofthe patient table during the medical imaging scan; performing a motiontracking analysis of the image sequence to extract a motion model,wherein at least one of the motion tracking analysis or the motion modelis tailored to the body region of interest and takes into account the atleast one of the current position or the current velocity of the patienttable; analysing the motion model to detect motion of the subject; andin response to the detected motion being above a threshold, at least oneof adapting the medical imaging examination to the detected motion orissuing an alert to make at least one of the subject or an operator ofthe medical imaging system aware of the detected motion.
 2. The methodof claim 1, wherein the motion tracking analysis uses a motion model,which is specific to at least one of the scan protocol or the bodyregion of interest.
 3. The method of claim 1, wherein the motiontracking analysis comprises: detecting and tracking landmarks specificto the body region of interest in the image sequence; applying a filteralgorithm to the landmarks to compensate for inaccurate detections inone or more images of the image sequence; correcting the landmarks bythe at least one of the current position or the current velocity of thepatient table; and estimating the motion model based on the filtered andcorrected landmarks; wherein the filter algorithm is a Kalman filter. 4.The method of claim 3, wherein the motion tracking analysis comprises:estimating rotation and translation vectors based on positions of thelandmarks on each image of the image sequence and parameters of thecamera; and determining an orientation and movement of the body regionof interest based on the landmarks and the rotation and translationvectors; wherein the body region of interest is the head of the subject.5. The method of claim 1, wherein the motion tracking analysis isstarted only once the patient table has reached a target position forthe medical imaging examination.
 6. The method of claim 1, wherein themotion tracking analysis comprises: correcting the motion model byestimating a translation using the at least one of the current positionor the current velocity of the patient table; wherein the correcting themotion model includes correcting a position of landmarks and motionvectors.
 7. The method of claim 1, wherein the body region of interestis the thorax, the camera is a three-dimensional camera, and the motiontracking analysis includes extracting a one-dimensional model of upwardsand downwards motion of the thorax from the image sequence.
 8. Themethod of claim 1, wherein the motion tracking analysis comprises:applying a dense motion tracking approach to the image sequence toestimate a dense motion vector field, wherein the dense motion vectorfield is calculated first in a coarse resolution, and then in one ormore finer resolutions, and the dense motion tracking approach is anOptical Flow Technique.
 9. The method of claim 8, wherein the bodyregion of interest is the thorax, and the motion tracking analysisincludes analysing an orientation of the dense motion vector field fordetecting inward and outward motion of the dense motion vector field,and estimating a motion model of breathing motion, and wherein theanalysing an orientation of the dense motion vector field includescalculating a divergence of the dense motion vector field.
 10. Themethod of claim 1, wherein the alert issued to the subject includes atleast one of a kind of motion or a suggestion for correcting the motion.11. The method of claim 1, wherein adapting the medical imagingexamination comprises: re-acquiring medical imaging data compromised bythe detected motion.
 12. The method of claim 1, wherein adapting themedical imaging examination comprises: performing a motion-compensatedmedical image reconstruction.
 13. The method of claim 1, wherein themedical imaging examination is a computed tomography examination, themedical imaging scan is a computed tomography scan, and the medicalimaging system is a computed tomography system.
 14. The method of claim1, wherein the medical imaging examination is a magnetic resonanceimaging examination, the medical imaging scan is a magnetic resonanceimaging scan, and the medical imaging system is a magnetic resonanceimaging system.
 15. A non-transitory computer-readable storage mediumencoded with programming instructions, wherein the programminginstructions are loadable into a computer system of a medical imagingsystem and, when executed, cause said computer system to carry out themethod of claim
 1. 16. A medical imaging system adapted to perform amedical imaging examination of a subject, the medical imagingexamination including a medical imaging scan of a body region ofinterest using a scan protocol, the medical imaging system furtheradapted to perform the method according to claim 1, and the medicalimaging system comprising: a gantry; a patient table configured to movewith respect to the gantry; a camera in a position and orientation withrespect to the gantry, the camera configured to acquire an image seriesof a subject positioned on the patient table; and a control unitconfigured to control a medical imaging scan, the control unit furtherconfigured to receive an image sequence of the subject from the cameraduring the medical imaging scan, receive at least one of a currentposition or a current velocity of the patient table during the medicalimaging scan, perform a motion tracking analysis of the image sequenceto extract a motion model, wherein at least one of the motion trackinganalysis or the motion model is tailored to the body region of interestand takes into account the at least one of the current position or thecurrent velocity of the patient table, analyze the motion model todetect motion of the subject, and in response to the detected motionbeing above a threshold, at least one of adapt the medical imagingexamination to the detected motion or issue an alert to make at leastone of the subject or an operator of the medical imaging system aware ofthe detected motion.
 17. The medical imaging system of claim 16, whereinthe camera is (i) a video camera or digital camera configured to acquiretwo-dimensional images or (ii) a three-dimensional camera configured toacquire images including depth information of the subject.
 18. Themedical imaging system of claim 16, wherein the medical imagingexamination is a computed tomography examination, the medical imagingscan is a computed tomography scan, and the medical imaging system is acomputed tomography system.
 19. The medical imaging system of claim 16,wherein the medical imaging examination is a magnetic resonance imagingexamination, the medical imaging scan is a magnetic resonance imagingscan, and the medical imaging system is a magnetic resonance imagingsystem.